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Robust Reconstruction of Interior Building Structures with Multiple Rooms under Clutter and Occlusions

Claudio Mura, Oliver Mattausch, Alberto Jaspe Villanueva, Enrico Gobbetti, and Renato Pajarola

November 2013

Abstract

We present a robust approach for reconstructing the architectural structure of complex indoor environments given a set of cluttered input scans. Our method first uses an efficient occlusion-aware process to extract planar patches as potential wall segments, separating them from clutter and coping with missing data. Using a diffusion process to further increase its robustness, our algorithm is able to reconstruct a clean architectural model from those potential wall segments. To our knowledge, this is the first indoor reconstruction method which goes beyond a binary classification and auto- matically recognizes different rooms as separate components. We demonstrate the validity of our approach by testing it on both synthetic models and real-world 3d scans of indoor environments.

Reference and download information

Claudio Mura, Oliver Mattausch, Alberto Jaspe Villanueva, Enrico Gobbetti, and Renato Pajarola. Robust Reconstruction of Interior Building Structures with Multiple Rooms under Clutter and Occlusions. In Proc. 13th International Conference on Computer-Aided Design and Computer Graphics. Pages 52-59, November 2013. IEEE. http://dx.doi.org/10.1109/CADGraphics.2013.14.

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Bibtex citation record

@InProceedings{Mura:2013:RRI,
    author = {Claudio Mura and Oliver Mattausch and Alberto {Jaspe Villanueva} and Enrico Gobbetti and Renato Pajarola},
    title = {Robust Reconstruction of Interior Building Structures with Multiple Rooms under Clutter and Occlusions},
    booktitle = {Proc. 13th International Conference on Computer-Aided Design and Computer Graphics},
    pages = {52--59},
    publisher = {IEEE},
    month = {November},
    year = {2013},
    abstract = { We present a robust approach for reconstructing the architectural structure of complex indoor environments given a set of cluttered input scans. Our method first uses an efficient occlusion-aware process to extract planar patches as potential wall segments, separating them from clutter and coping with missing data. Using a diffusion process to further increase its robustness, our algorithm is able to reconstruct a clean architectural model from those potential wall segments. To our knowledge, this is the first indoor reconstruction method which goes beyond a binary classification and auto- matically recognizes different rooms as separate components. We demonstrate the validity of our approach by testing it on both synthetic models and real-world 3d scans of indoor environments. },
    url = {http://vic.crs4.it/vic/cgi-bin/bib-page.cgi?id='Mura:2013:RRI'},
}